Zenon Pylyshyn

In _Seeing and Visualizing_, Zenon Pylyshyn argues that seeing is different from thinking and that to see is not, as it may seem intuitively, to create an inner replica of the world. Pylyshyn examines how we see and how we visualize and why the scientific account does not align with the way these processes seem to us "from the inside." In doing so, he addresses issues in vision science, cognitive psychology, philosophy of mind, and cognitive neuroscience. First, Pylyshyn argues that there is a core stage of vision independent from the influence of our prior beliefs and examines how vision can be intelligent and yet essentially knowledge-free. He then proposes that a mechanism within the vision module, called a visual index (or FINST), provides a direct preconceptual connection between parts of visual representations and things in the world, and he presents various experiments that illustrate the operation of this mechanism. He argues that such a deictic reference mechanism is needed to account for many properties of vision, including how mental images attain their apparent spatial character without themselves being laid out in space in our brains. The final section of the book examines the "picture theory" of mental imagery, including recent neuroscience evidence, and asks whether any current evidence speaks to the issue of the format of mental images. This analysis of mental imagery brings together many of the themes raised throughout the book and provides a framework for considering such issues as the distinction between the form and the content of representations, the role of vision in thought, and the relation between behavioral, neuroscientific, and phenomenological evidence regarding mental representations.

In _Things and Places_, Zenon Pylyshyn argues that the process of incrementally constructing perceptual representations, solving the binding problem (determining which properties go together), and, more generally, grounding perceptual representations in experience arise from the nonconceptual capacity to pick out and keep track of a small number of sensory individuals. He proposes a mechanism in early vision that allows us to select a limited number of sensory objects, to reidentify each of them under certain conditions as the same individual seen before, and to keep track of their enduring individuality despite radical changes in their properties -- all without the machinery of concepts, identity, and tenses. This mechanism, which he calls FINSTs (for "Fingers of Instantiation"), is responsible for our capacity to individuate and track several independently moving sensory objects -- an ability that we exercise every waking minute, and one that can be understood as fundamental to the way we see and understand the world and to our sense of space. Pylyshyn examines certain empirical phenomena of early vision in light of the FINST mechanism, including tracking and attentional selection. He argues provocatively that the initial selection of perceptual individuals is our primary nonconceptual contact with the perceptual world (a contact that does not depend on prior encoding of any properties of the thing selected) and then draws upon a wide range of empirical data to support a radical externalist theory of spatial representation that grows out of his indexing theory.

This study investigates a new experimental paradigm called the Modified Traveling Salesman Problem. This task requires subjects to visit once and only once n invisible targets in a 2D display, using a virtual vehicle controlled by the subject. Subjects can only see the directions of the targets from the current location of the vehicle, displayed by a set of oriented segments that can be viewed inside a circular window surrounding the vehicle. Two conditions were compared. In the “allocentric” condition, subjects see the vehicle move across the screen and change orientation under their command. The “egocentric” condition is similar except for how the information is provided: the position and orientation of the vehicle icon remains fixed at the center of the screen and only target directions, as indicated by the oriented segments, change as the subject “moves” the vehicle. The unexpected finding was that this task can be performed, in either condition, for up to 10 targets. We consider two possible strategies that might be used, a location-based strategy and a segment strategy. The location-based strategy relies on spatial memory and attempts to infer the locations of all the targets. The segment strategy is more local and focuses on the directional segments themselves, keeping track of the ones that represent already-visited targets. A number of observations suggest that the segment strategy was used, at least for larger numbers of targets. According to our hypothesis, keeping track of the segments requires one to use indexical reference for associating the segments with their status in the task - given by current status predicates Visited or Not-visited -, perhaps using visual indexes, deictic pointers, or object files.

This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation.

Using a novel enumeration task, we examined the encoding of spatial information during subitizing. Observers were shown masked presentations of randomly-placed discs on a screen and were required to mark the perceived locations of these discs on a subsequent blank screen. This provided a measure of recall for object locations and an indirect measure of display numerosity. Observers were tested on three stimulus durations and eight numerosities. Enumeration performance was high for displays containing up to six discs—a higher subitizing range than reported in previous studies. Error in the location data was measured as the distance between corresponding stimulus and response discs. Overall, location errors increased in magnitude with larger numerosities and shorter display durations. When errors were computed as disc distance from display centroid, results suggest a compressed representation by observers. Additionally, enumeration and localization accuracy increased with display regularity.

��In four experiments we address the question whether several visual objects can be selected voluntarily (exogenously) and then tracked in a Multiple Object Tracking paradigm and, if so, whether the selection involves a different process. Experiment 1 showed that items can indeed be selected based on their labels. Experiment 2 showed that to select the complement set to a set that is automatically (exogenously) selected — e.g. to select all objects not flashed — observers require additional time and that given 1080 ms they were able to select and track them as well as those selected automatically. Experiment 3 showed that the additional time needed in the previous experiment cannot be attributed solely to time required to disengage attention from the initially automatic selections. Experiment 4 showed that the added time provides a monotonically greater benefit when there are more targets, suggesting a serial process. These results are discussed in relation to the Visual Index (FINST) theory which assumes that visual indexes are captured by a data-driven process. It is suggested that voluntarily allocated attention can be used to facilitate the automatic attention capture by objects of interest.

People have always wondered how thinking takes place and what thoughts are constructed from. We typically experience our thoughts as involving pictorial (or sensory) contents or as being in words. Although this idea has been enshrined in psychology as the “dual code” theory of reasoning and memory, serious questions have been raised concerning this view. It appears that whatever the form of our thoughts it is unlikely that it is anything like our experience of them. But if thought is not in pictures or words, what form does it take? If we do not sometimes think in words, then what actually goes on when we think by engaging in an “inner dialogue”? And if we do not sometimes think in pictures, what goes on when we reason by creating and examining “mental images”?

You might reasonably surmise from the title of this paper that I will be discussing a theory of vision. After all, what is a theory of vision but a theory of how the world is connected to our visual representations? Theories of visual perception universally attempt to give an account of how a proximal stimulus (presumably a pattern impinging on the retina) can lead to a rich representation of a three dimensional world and thence to either the recognition of known objects or to the coordination of actions with visual information. Such theories typically provide an effective (i.e., computable) mapping from a 2D pattern to a representation of a 3D scene, usually in the form of a symbol structure. But such a mapping, though undoubtedly the essential purpose of a theory of vision, leaves at least one serious problem that I intend to discuss here. It is this problem, rather than a theory of vision itself, that is the subject of this talk

This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking. 1 The Explanatory Vocabulary of Cognition 2 The Explanatory Role of Representations 3 The Relevance of Computation 4 The Psychological Reality of Programs: Strong Equivalence 5 Constraining Functional Architecture 6 The Bridge from Physical to Symbolic: Transduction 7 Functional Architecture and Analogue Processes 8 Mental Imagery and Functional Architecture 9 Epilogue: What is Cognitive Science the Science of?

In the past decade there has been renewed interest in the study of mental imagery. Emboldened by new findings from neuroscience, many people have revived the idea that mental imagery involves a special format of thought, one that is pictorial in nature. But the evidence and the arguments that exposed deep conceptual and empirical problems in the picture theory over the past 300 years have not gone away. I argue that the new evidence from neural imaging and clinical neuropsychology does little to justify this recidivism because it does not address the format of mental images. I also discuss some reasons why the picture theory is so resistant to counterarguments and suggest ways in which non-pictorial theories might account for the apparent spatial nature of images.

In three experiments, subjects attempted to track multiple items as they moved independently and unpredictably about a display. Performance was not impaired when the items were briefly (but completely) occluded at various times during their motion, suggesting that occlusion is taken into account when computing enduring perceptual objecthood. Unimpaired performance required the presence of accretion and deletion cues along fixed contours at the occluding boundaries. Performance was impaired when items were present on the visual field at the same times and to the same degrees as in the occlusion conditions, but disappeared and reappeared in ways which did not implicate the presence of occluding surfaces (e.g. by imploding and exploding into and out of existence, instead of accreting and deleting along a fixed contour). Unimpaired performance did not require visible occluders (i.e. Michotte’s tunnel effect) or globally consistent occluder positions. We discuss implications of these results for theories of objecthood in visual attention.

Although the study of visual perception has made more progress in the past 40 years than any other area of cognitive science, there remain major disagreements as to how closely vision is tied to general cognition. This paper sets out some of the arguments for both sides and defends the position that an important part of visual perception, which may be called early vision or just vision, is prohibited from accessing relevant expectations, knowledge and utilities - in other words it is cognitively impenetrable. That part of vision is complex and articulated and provides a representation of the 3-D surfaces of objects sufficient to serve as an index into memory, with somewhat different outputs being made available to other systems such as those dealing with motor control. The paper also addresses certain conceptual and methodological issues, including the use of signal detection theory and event-related potentials to assess cognitive penetration of vision. A distinction is made among several stages in visual processing. These include, in addition to the inflexible early-vision stage, a pre-perceptual attention allocation stage and a post-perceptual evaluation, memory-accessing, and inference stage which provide several different highly constrained ways in which cognition can affect the outcome of visual perception. The paper discusses arguments that have been presented in both computer vision and psychology showing that vision is "intelligent" and involves elements of problem solving". It is suggested that these cases do not show cognitive penetration, but rather they show that certain natural constraints on interpretation, concerned primarily with optical and geometrical properties of the world, have been compiled into the visual system. The paper also examines a number of examples where instructions and "hints" are alleged to affect

The target article claimed that although visual apprehension involves all of general cognition, a significant component of vision (referred to as early vision) works independently of cognition and yet is able to provide a surprisingly high level interpretation of visual inputs, roughly up to identifying general shape-classes. The commentators were largely sympathetic, but frequently disagreed on how to draw the boundary, on exactly what early vision delivers, on the role that attention plays, and on how to interpret the neurophysiological data showing top-down effects. A significant number simply asserted that they were not willing to accept any distinction between vision and cognition, and a surprising number even felt that we could never tell for sure, so why bother? Among the topics covered was the relation of cognition and consciousness, the relation of early vision to other modules such as face recognition and language, and the role of natural constraints.

This commentary argues that the “illusion” to which Wegner refers in The Illusion of Conscious Will is actually the illusion that our conscious experience of mentally causing certain behaviors explains the behavior in question: It is not the subjective experience itself that is illusory, but the implied causal explanation. The experience of “mental effort” is cited as another example of this sort of illusion. Another significant example is the experience that properties of the representation of our mental images are responsible for certain patterns of behavior observed in mental imagery experiments. Examples include the increase in reaction time found when details are reported from smaller images or when attention is switched between different places and features (imagined as further apart than they are) within a single image. These examples illustrate the nature of the “illusion” involved: It is the illusion that certain observed regularities occur because of the content of the experience, as opposed to the converse – that experience has the content it does because of what the person figures out would happen in the imagined situation.